IDEAS home Printed from https://ideas.repec.org/p/boc/wsug07/14.html
   My bibliography  Save this paper

Multilevel modeling of complex survey data

Author

Listed:
  • Sophia Rabe-Hesketh

    (University of California, Berkeley)

Abstract

Survey data are often analyzed using multilevel or hierarchical models. For example, in education surveys, schools may be sampled at the first stage and students at the second stage and multilevel models used to model within-school and between-school variability. An important aspect of most surveys that is often ignored in multilevel modeling is that units at each stage are sampled with unequal probabilities. Standard maximum likelihood estimation can be modified to take the sampling probabilities into account, yielding pseudomaximum likelihood estimation, which is typically combined with robust standard errors based on the sandwich estimator. This approach is implemented in gllamm. I will introduce the ideas, discuss issues that arise such as the scaling of the weights, and illustrate the approach by applying it to data from the Program for International Student Assessment (PISA).

Suggested Citation

  • Sophia Rabe-Hesketh, 2007. "Multilevel modeling of complex survey data," West Coast Stata Users' Group Meetings 2007 14, Stata Users Group.
  • Handle: RePEc:boc:wsug07:14
    as

    Download full text from publisher

    File URL: http://repec.org/wcsug2007/stata_sophia.pdf
    File Function: presentation slides
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    2. Anders Skrondal & Sophia Rabe-Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. José Ernesto Amorós Espinosa & Luciano Ciravegna & Vesna Mandakovic & Pekka Stenmolm, 2017. "Necessity or opportunity? the effects of State fragility and economic development on entrepreneurial efforts," Serie Working Papers 42, Universidad del Desarrollo, School of Business and Economics.
    2. Diana M. Hechavarría & Siri A. Terjesen & Amy E. Ingram & Maija Renko & Rachida Justo & Amanda Elam, 2017. "Taking care of business: the impact of culture and gender on entrepreneurs’ blended value creation goals," Small Business Economics, Springer, vol. 48(1), pages 225-257, January.
    3. Alinne Veiga & Peter W. F. Smith & James J. Brown, 2014. "The use of sample weights in multivariate multilevel models with an application to income data collected by using a rotating panel survey," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 65-84, January.
    4. Johnson, Michelle A. & Marchi, Kristen S., 2009. "Segmented assimilation theory and perinatal health disparities among women of Mexican descent," Social Science & Medicine, Elsevier, vol. 69(1), pages 101-109, July.
    5. Ana Maria Osorio & Catalina Bolancé & Nyovane Madise & Katharina Rathmann, 2013. "Social Determinants of Child Health in Colombia: Can Community Education Moderate the Effect of Family Characteristics?," Working Papers XREAP2013-02, Xarxa de Referència en Economia Aplicada (XREAP), revised Mar 2013.
    6. Greeson, Johanna K.P. & Usher, Lynn & Grinstein-Weiss, Michal, 2010. "One adult who is crazy about you: Can natural mentoring relationships increase assets among young adults with and without foster care experience?," Children and Youth Services Review, Elsevier, vol. 32(4), pages 565-577, April.
    7. Kathryn M. Yount & AliceAnn Crandall & Yuk Fai Cheong & Theresa L. Osypuk & Lisa M. Bates & Ruchira T. Naved & Sidney Ruth Schuler, 2016. "Child Marriage and Intimate Partner Violence in Rural Bangladesh: A Longitudinal Multilevel Analysis," Demography, Springer;Population Association of America (PAA), vol. 53(6), pages 1821-1852, December.
    8. Amini, Chiara & Commander, Simon, 2012. "Educational scores: How does Russia fare?," Journal of Comparative Economics, Elsevier, vol. 40(3), pages 508-527.
    9. Li Yu & Peter F. Orazem, 2014. "O-Ring production on U.S. hog farms: joint choices of farm size, technology, and compensation," Agricultural Economics, International Association of Agricultural Economists, vol. 45(4), pages 431-442, July.
    10. Nathaniel J.S. Ashby & Lukasz Walasek & Andreas Glöckner, 2015. "The effect of consumer ratings and attentional allocation on product valuations," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(2), pages 172-184, March.
    11. Tso, Geoffrey K.F. & Guan, Jingjing, 2014. "A multilevel regression approach to understand effects of environment indicators and household features on residential energy consumption," Energy, Elsevier, vol. 66(C), pages 722-731.
    12. Herzfeld, Thomas & Huffman, Sonya & Rizov, Marian, 2014. "The dynamics of food, alcohol and cigarette consumption in Russia during transition," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 128-143.
    13. Brumback, Babette A. & He, Zhulin, 2011. "The Mantel-Haenszel estimator adapted for complex survey designs is not dually consistent," Statistics & Probability Letters, Elsevier, vol. 81(9), pages 1465-1470, September.
    14. Spriggs, Aubrey L. & Halpern, Carolyn Tucker & Herring, Amy H. & Schoenbach, Victor J., 2009. "Family and school socioeconomic disadvantage: Interactive influences on adolescent dating violence victimization," Social Science & Medicine, Elsevier, vol. 68(11), pages 1956-1965, June.
    15. Simon COMMANDER & Natalia ISACHENKOVA & Yulia RODIONOVA, 2013. "Informal employment dynamics in Ukraine: An analytical model of informality in transition economies," International Labour Review, International Labour Organization, vol. 152(3-4), pages 445-467, December.
    16. Amini, Chiara & Nivorozhkin, Eugene, 2015. "The urban–rural divide in educational outcomes: Evidence from Russia," International Journal of Educational Development, Elsevier, vol. 44(C), pages 118-133.
    17. Elena Pirani & Silvana Salvini, 2012. "Socioeconomic Inequalities and Self-Rated Health: A Multilevel Study of Italian Elderly," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 31(1), pages 97-117, February.
    18. Murasko, Jason E., 2013. "Associations between household income, height, and BMI in contemporary US schoolchildren," Economics & Human Biology, Elsevier, vol. 11(2), pages 185-196.
    19. Sophia Rabe-Hesketh & Anders Skrondal, 2007. "Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 123-140, June.
    20. Michele Battisti & Andrea Mario Lavezzi & Lucio Masserini & Monica Pratesi, 2014. "Resisting to the Extortion Racket: an Empirical Analysis," Working Papers LuissLab 14115, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    21. Yang, Tingzhong & Barnett, Ross & Jiang, Shuhan & Yu, Lingwei & Xian, Hong & Ying, Jun & Zheng, Weijun, 2016. "Gender balance and its impact on male and female smoking rates in Chinese cities," Social Science & Medicine, Elsevier, vol. 154(C), pages 9-17.
    22. Bowen, Mary Elizabeth, 2009. "Childhood socioeconomic status and racial differences in disability: Evidence from the Health and Retirement Study (1998-2006)," Social Science & Medicine, Elsevier, vol. 69(3), pages 433-441, August.
    23. Yu, Li, 2008. "Three essays on technology adoption, firm size, wages and human capital," ISU General Staff Papers 2008010108000016715, Iowa State University, Department of Economics.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:boc:wsug07:14. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum). General contact details of provider: http://edirc.repec.org/data/stataea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.